As integrated circuit device densities continue to increase and correspondingly device and circuit dimensions continue to decrease, wafer inspection systems for macro-defect detection, primarily used in the lithography steps of wafer manufacture, must move to higher resolution. This will preferably be accomplished while maintaining the extremely high throughput achieved by currently available inspection systems. By way of example, the KLA-Tencor 2430 inspection system is a 300-mm capable inspector, with a throughput of up to 100 to 140 wafers per hour. Since at present, most macroscopic defects of interest are in the 30 micron and above size range, the 2430 is designed to have a pixel size of 39 microns, which achieves 30 to 50 micron defect detection, depending on the defect type and the background. However, with the downward evolution of device dimensions, there is currently strong interest in increasing the resolution of the system so as to detect defects in the 10 micron size range, while maintaining the throughput of the current system.
Microarray scanners produce images composed of a matrix of pixels, where each represents the intensity of light emanating from a small illuminated area of the sample. The scanner for detection systems such as the KLA-Tencor 2430 system is a CCD scanner with the sample illumination being line illumination using a source such as shaped fiber optics from a lamp. It is comprised of an array of sensors, each of which is a photodiode which produces electron-hole pairs when a photon is incident, thereby causing a charge build-up. Adjacent photo-diode sensors are separated by isolation such as trench isolation. FIG. 1 illustrates incident light 100 impinging on sample 110, with outgoing light from the sample (which may be reflected, scattered, or diffracted light) passing through optical elements 120 to sensor array 130 comprising sensors 140.
System resolution is derived from both pixel resolution and optical resolution. The pitch of the detector elements or sensors determines pixel resolution, since each pixel integrates the incoming signal over its area. Optical resolution is determined by the performance of optical elements 120. It is possible to increase system resolution, i.e., to resolve smaller defects on the sample surface, by several methods, including: 1) the pixel size may be held constant, but a larger sensor array containing more pixels (sensors) may be used, with the optical elements acting to spread the outgoing light from the sample onto the larger array area, or 2) the sensor array may be held at a constant size, but the number of pixels may be increased by decreasing the sensor size and pitch. Each of these methods has drawbacks:
1) The size of the sensor array is limited mainly by photolithography considerations. The yield of the sensor array is considerably higher if it is fabricated in a single lithography step, which for current processing methods limits the array size to about 75 mm.
2) A lower limit to pixel size is imposed by an effect known as Schott noise, which is the variation in charge build-up in a sensor for each sampling time. The Schott noise is proportional to the square root of the number of electrons, whereas the photodiode signal is proportional to the number of electrons. Therefore, the signal-to-noise ratio decreases as the number of electrons decreases. This effect is unavoidable and is a consequence of the Poisson statistics that govern electrons. The well capacity of a photodiode sensor (maximum number of electrons stored therein) is determined by the capacitance of the photodiode, which is in turn proportional to the area of the photosensor. By way of example, the present sensor element used in the KLA-Tencor 2430 system is of nine square micron size, and has a capacity of about 400 K electrons per well. A next generation sensor of 7 square micron size has a capacity of about 250 K electrons per well, with correspondingly greater (percentually) Schott noise. Accordingly, the greater resolution afforded by decreasing pixel size is accompanied by poorer signal to noise ratio. Averaging over repeated measurements can reduce Schott noise, but this technique lowers throughput.
An important improvement for defect detection systems would be a reduction in effective pixel size, or alternatively an increase in the effective number of pixels per unit area of the sensor array, while avoiding increased Schott noise. In either case, this would allow better sampling of the sample surface, to see higher frequency effects such as smaller defect sizes, and also to avoid aliasing. For example, according to the Nyquist theorem, in order to reconstruct a real signal for a feature without getting an aliasing effect, at least two samplings are required across the feature; i.e., the sampling frequency must be at least double the feature frequency. Descriptions of aliasing and related effects can be found in: Digital Image processing and Computer Vision, Robert J. Schalkoff, John Wiley and Sons, 1989, pp 112 ff, and in Digital Image Processing, Rafael C. Gonzalez and Richard E. Woods, Addison Wesley, 1992, pp 112ff.